4 ways Tunnels.ai is changing the Tunnelling Industry using Artificial Intelligence and Big Data

Tunnels.ai is an ambitious community driven project powered through a global community of Civil Engineers. The project centralises publicly available data and allows powerful artificial intelligence algorithms behind the scenes to make design and construction predictions, guiding Engineers to reach the best decisions. The most remarkable thing about tunnels.ai is it is completely free and promotes global collaboration and sharing of knowledge to create a ‘hive mind’ of tunnelling expertise. In this article we briefly cover 4 ways in which tunnels.ai is revolutionising the tunnelling industry.


1.      Predicting tunnel lining designs

Historically, Civil Engineers have relied on the expertise of a select group of Senior Engineers with past project experience to guide them in the selection of an outline structural design in the early stages of a Tunnelling project. Tunnels.ai offers a different approach to this and has developed a tool collecting together over 480 tunnel project references in 148 cities and 47 countries worldwide to make artificial intelligence powered design predictions for tunnel lining designs, boasting a 95% confidence level in it’s prediction. This tool allows Engineers to make predictions of key parameters such as tunnel lining thickness, tunnel ring length, number of segments in a ring and more. The results of the tools prediction are compiled elegantly into a well presented feasibility report, ready for the Engineer to share with others on the project. Try out a predicting a tunnel lining design here.

Predicting tunnel lining designs

2.      Predicting project costs

Tunnelling project costs have traditionally been incredibly difficult to predict, with uncertainty over unforeseen ground conditions and unexpected project delays affecting costs. Cost predictions are further complicated globally due to significant differences in costs associated with local market labour costs, geological conditions, tunnelling method selected and tunnel size specified, with these varying significantly from project to project. Tunnels.ai have developed an artificial intelligence which uses trends in publicly available data, capable of predicting tunnel costs per m within any global region, with estimates available in US dollars, Great British Pounds and Euros. Tunnelling costs can be estimated for TBM tunnelling, mining and cut and cover methods with results generated comparing across different regions, geological conditions and tunnelling methods. Try out predicting a tunnel cost here.

3.      Predicting carbon emissions

Sustainability has never been more important than it is today and tunnel construction can be a source of significant carbon dioxide contributions mainly resulting from the vast volume of concrete needed in construction of a tunnel. Tunnels.ai have developed a tool to estimate the carbon dioxide emissions resulting from tunnel construction using the latest peer reviewed Carbon prediction methods. Artificial intelligence is then used to suggest to the Engineer whether the design and materials could be optimised to reduce the project carbon footprint, prompting the Engineer to consider the sustainability impacts of their design. Try out predicting your tunnel project carbon emissions here.

4.      Predicting mined tunnel designs

Mined tunnelling has often been regarded as a high-risk activity in the construction industry and proper design and consideration of prevailing geological conditions is of upmost importance. Tunnels.ai have developed a tool capable of predicting mined tunnel designs using the RMR and Q System methods giving Engineers a better initial understanding of likely support requirements before proceeding to detailed design. Try out predicting a mining design here.